Senior/Staff Data Scientist

FloatMe

Senior/Staff Data Scientist transforming product, customer, and risk data into actionable insights. Leading analysis, experimentation, forecasting, and visualization in a fintech startup environment.

Posted 7/30/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $150,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in applying AI, machine learning, and statistical modeling to drive decision-making in product and risk contexts. Proficient in SQL and Python for data analysis and visualization, with a strong ability to communicate insights to diverse stakeholders.

Highest-signal resume keywords

AI ApplicationMachine LearningStatistical ModelingSQL ProficiencyData Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AIMachine LearningStatistical ModelingSQLPythonData AnalysisMetrics DefinitionExperimentationForecastingDecision Support

Soft Skills

Analytical JudgmentCommunicationCollaborationProblem-Solving

Certifications & Qualifications

Master's DegreePhD Degree

Industry Keywords

CreditRiskFraudRecommendationsCustomer Outcomes

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

You will turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners
Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support
Define and maintain measurement frameworks for FloatMe products, including customer eligibility, repayment behavior, product usage, loss performance, funnel health, subscription, and long-term customer outcomes
Partner with Machine Learning Engineers (MLEs) to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact
Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth
Approach ambiguous product and risk questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria
Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers
Lead technical direction and standards - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others
Drive localized cross-team impact by partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy

Requirements

What you’ll need

4+ years applying AI, machine learning, or statistical modeling in decisioning contexts such as credit, risk, fraud, recommendations, or similar domains.
A Master degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Computer Science, Operation Research). A PhD degree is welcomed.
Advanced proficiency with SQL, Python and experience building clear, decision-oriented data visualizations
Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions
Experience using AI tools to improve the speed, quality, and durability of analytical work.

Benefits

Comp & perks

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